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Model for Prediction of the Weight and Height Measurements of Patients with Disabilities for Diagnosis and Therapy
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Background: Accurate measurement of a patient’s height and weight is an essential part of diagnosis and therapy, but there is some controversy as to how to calculate the height and weight of patients with disabilities. Objective: This study aims to use anthropometric measurements (arm span, length of leg, chest circumference, and waist circumference) to find a model (alternatives) that can allow the calculation of the height and the body weight of patients with disabilities. Additionally, a model for the prediction of weight and height measurements of patients with disabilities was established. Method: Four hander patients aged 20-80 years were enrolled in this study and divided into two groups, 210 (52.5%) male and 190 (47.5%) female. Result: A significant correlation was noted between body height and arm span, as well as between body height and length of leg in all study groups. The body weight and the ratio of arm span or leg length to the sum of chest and waist circumferences were found to have a negative significant correlation. Model equations were derived to estimate the height and body weight according to anthropometric measurements. Conclusion: Anthropometric measurements can be used to create a model for calculating the body height and body weight of patients with disabilities and which can be considered an alternative to measurements that can be made on otherwise healthy subjects.

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Publication Date
Sun Jul 01 2012
Journal Name
Applied Soft Computing
A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks
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Publication Date
Sun Oct 01 2023
Journal Name
Ieee Transactions On Industrial Electronics
Singular Perturbation-Based Adaptive Integral Sliding Mode Control for Flexible Joint Robots
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The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha

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Publication Date
Sun Oct 20 2024
Journal Name
Chemical Papers
Response surface methodology for optimizing crude oil desalting unit performance in iraq
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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Construction Engineering And Management
Developing a Decision-Making Framework to Select Safety Technologies for Highway Construction
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Publication Date
Sun Jun 21 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Co-Amorphous System: A promising Strategy for Delivering Poorly Water - Soluble Drugs
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Amorphization of drug has been considered as an attractive approach in improving drug solubility and bioavailability. Unlike their crystalline counterparts, amorphous materials lack the long-range order of molecular packing and present the highest energy state of a solid material. Co-amorphous systems (CAM) are an innovative formulation technique by where the amorphous drugs are stabilized via powerful intermolecular interactions by means of a low molecular co-former.

This review highlights the different approaches in the preparation of co-amorphous drug delivery system, the proper selection of the co-formers. In addition, the recent advances in characterization, Industrial scale and formulation will be discussed.

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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
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High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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Publication Date
Tue Feb 05 2019
Journal Name
Journal Of The College Of Education For Women
The study of physical and chemical properties of wells water in district of Samarra
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The Study was achieved adjectives physical and chemical water wells in the district of
Samarra , where a study has 42 sample groundwater in different regions of the judiciary
randomly distributed all over the judiciary and examined in vitro.
The study showed that the quality of groundwater in the general area of study
Kipritateh punctuated Klordih water quality and other quality Bicarboonatih.
Varied the key components of groundwater in the study area in concentrations
between periods of rain and drought, especially because of the cation ion exchange processes
as well as mitigation as a result of filtering rain water and dominated the calcium ion,
followed by sodium.
As for the negative ions has dominated ion s

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Significance and Conservation of Birds of the Genus of Bee-eater (MEROPS) in Uzbekistan
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The purpose of this article is to identify and evaluate the importance of birds of the genus Merops (European Bee-eater -Merops apiaster and Blue-cheeked Bee-eater -Merops persicus) in Uzbekistan, as well as to develop recommendations aimed at solving some problems associated with its conservation. As a result of the study, in the aspect of biocenotic relations, the natural significance of these species was revealed. The economic value is determined and analyzed in beekeeping farms. From the study of the remains of food contained in the stomachs, throats and nests of M.apiaster, a preliminary list of the main species of the food spectrum has been compiled. Based on the bioacoustic repellent "Korshun-8"

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